-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathmaterials.qmd
100 lines (51 loc) · 3.73 KB
/
materials.qmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
---
title: "EEID 2024 Workshop Training Materials"
format:
html:
toc: true
toc-location: left
html-math-method: katex
css: styles.css
---
# Overview
Most of the materials here were initially developed as part of the [VectorByte Initiative](www.vectorbyte.org) and the older VectorBiTE RCN. As such, they have been developed with the effort of many people over the years. Most of the specific materials for this workshop were originally developed by [Dr. Leah R. Johnson](https://lrjohnson0.github.io/QEDLab/leahJ.html) and [Sean Sorek](https://lrjohnson0.github.io/QEDLab/seanS.html). They have been modified for this workshop by Leah Johnson and Victor Pena.
# Pre-work and set-up
## Hardware and Software
We will be using [`R`](https://cran.r-project.org/) for all data manipulation and analyses/model fitting. Any operating system (Windows, Mac, Linux) will do, as long as you have `R` (version 4.2 or higher) installed.
You may use any IDE/ GUI for `R` (VScode, RStudio, Emacs, etc). For most people, [`RStudio`](https://www.rstudio.com/) is a good option. Whichever one you decide to use, please make sure it is installed and test it before the workshop.
We will also be using a new package, [`bayesTPC`](https://www.biorxiv.org/content/10.1101/2024.04.25.591212v1). We suggest that you install this package in advance. Note that the `nimble` package must be installed and loaded before `bayesTPC` can be used. To install `bayesTPC` you can use the following code:
```{r, eval=FALSE}
remotes::install_github("johnwilliamsmithjr/bayesTPC")
```
## Pre-requisites
We are assuming familiarity with R basics as well as at least introductory statistics, including up through linear models and the idea of a likelihood. If you would like materials to review, we recommend that you do the following:
1. Go to [The Multilingual Quantitative Biologist](https://mhasoba.github.io/TheMulQuaBio/intro.html), and read+work through the [Biological Computing in R Chapter](https://mhasoba.github.io/TheMulQuaBio/notebooks/07-R.html).
2. In addition / alternatively to pre-work element (1), here are some resources for brushing up on R [at the end of the Intro R Chapter you can try](https://mhasoba.github.io/TheMulQuaBio/notebooks/07-R.html#readings-and-resources). But there are many more resources online (e.g., [this](https://www.codecademy.com/learn/learn-r) and [this](https://www.dataquest.io/blog/learn-r-for-data-science/) ) -- pick something that suits your learning style.
3. Review background on [introductory probability and statistics](Stats_review.qmd) ([solutions to exercises](Stats_review_soln.qmd)). You can also use the resources on [The Multilingual Quantitative Biologist - Basic Data Analyses and Statistics](https://mhasoba.github.io/TheMulQuaBio/Stats-Intro.html)
<br> <br>
# 2024 Training Materials
## Introduction to traits in Disease modeling
- [Lecture slides](intro_to_traits.pdf)
- [Cator *et al*. 2020. The Role of Vector Trait Variation in Vector-Borne Disease Dynamics](Cator2020.pdf)
<br> <br>
## Intro to Course Tools
- [Lecture Slides](EEID_Tools.qmd), [Practical](Intro_to_API.qmd)
<br> <br>
## Intro to Bayes
- [Lecture Slides](VB_Bayes1.qmd), [Practical](VB_Bayes_activity1.qmd)
- Datasets:
- [Midge data](MidgeWingLength.csv)
<br> <br>
## Bayesian computation and MCMC
- [Lecture Slides](VB_Bayes2.Qmd), [Practical](VB_Bayes_activity2.Qmd)
<br> <br>
## Fitting TPCs using `bayesTPC`
- [Practical](bayesTPC_activity.qmd)
<br> <br>
## Advanced features in `bayesTPC`
- [Practical](bayesTPC_advanced.qmd)
- Datasets:
- [Antibiotic data](ab_data.csv)
<br> <br>
----------------------------------------------
<center> {width=6cm} {width=6cm} </center>